tailieunhanh - COMPUTER-AIDED INTELLIGENT RECOGNITION TECHNIQUES AND APPLICATIONS phần 10

sử dụng các biện pháp khác ngoài các luật kết hợp DFC của chúng tôi, như độ sáng, có nghĩa là, phương sai, skewness và kurtosis cho hình ảnh phân đoạn DFC. Những biện pháp này đã được báo cáo có một số thành công trong việc xác định bất thường | Application 447 cosine approach and PSD approach respectively in the considered noisy environment q0 i q0 is a the signal noise ratio for the hypothesis H0 ay is the interference variance. When the level of interference is relatively low . at q0 10 dB the criterion of Equation coincides with that in Equation . The dependency between the Fisher criterion Equation and the signal noise ratio q0 is shown in Figure . We find from Equations - and Figure that the recognition effectiveness of the proposed approach as well as the recognition effectiveness of the Hartley approach depends only on the difference of the signal variances and the signal noise ratio. It can be seen from Equations - and Figure that the effectiveness of the proposed approach and the Hartley cosine and PSD approaches decreases with decrements of the signal noise ratio q0 . increments of the noise variance for arbitrary values of the parameter b however the use of the proposed approach in the considered noisy environment provides the same recognition effectiveness gain see Equations and as in the case without a noisy environment. 3. Application We apply the generalized approach to the intelligent recognition of object damping and fatigue. We consider the two-class diagnostics of the object damping ratio gj for hypothesis Hj using the forced oscillation diagnostic method 2 41 . The method which consists of exciting tested objects into resonant oscillations and recognition is based on the Fourier transform of the vibration resonant oscillations. The basis of the method is the fact that damping ratio changes will modify the parameters of the vibration resonant oscillations. The differential equation of motion for the tested object - a single degree of freedom linear oscillator under white Gaussian noise stationary excitation - is described as x 2 p nx mnx A f cos ự t . cj . where x is the object displacement G - m Cj k are .